Storage network with multiple storage types

ABSTRACT

A processing system of a storage network operates by: receiving a write request to store a data object; selecting a selected memory type of a plurality of memory types to store the data object, based on object parameters associated with the data object; selecting a selected memory to store the data object, the selected memory having the selected memory type of the plurality of memory types; and facilitating storage of the data object in the selected memory having the selected memory type of the plurality of memory types, wherein the data object is dispersed error encoded and stored as a plurality of encoded data slices.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility patent application claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No.17/079,891, entitled “STORAGE SYSTEM WITH MULTIPLE STORAGE TYPES IN AVAST STORAGE NETWORK”, filed Oct. 26, 2020, which is acontinuation-in-part of U.S. Utility application Ser. No. 16/244,615,entitled “ALLOCATING REBUILDING QUEUE ENTRIES IN A DISPERSED STORAGENETWORK”, filed Jan. 10, 2019, issued as U.S. Pat. No. 10,838,814 onNov. 17, 2020, which is a continuation of U.S. Utility application Ser.No. 15/439,383, entitled “ALLOCATING REBUILDING QUEUE ENTRIES IN ADISPERSED STORAGE NETWORK”, filed Feb. 22, 2017, issued as U.S. Pat. No.10,241,866 on Mar. 26, 2019, which is a continuation-in-part of U.S.Utility application Ser. No. 15/095,558, entitled “ACHIEVING STORAGECOMPLIANCE IN A DISPERSED STORAGE NETWORK”, filed Apr. 11, 2016, issuedas U.S. Pat. No. 10,013,203 on Jul. 3, 2018, which is acontinuation-in-part of U.S. Utility application Ser. No. 14/088,794,entitled “ACHIEVING STORAGE COMPLIANCE IN A DISPERSED STORAGE NETWORK”,filed Nov. 25, 2013, issued as U.S. Pat. No. 9,311,187 on Apr. 12, 2016,which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. ProvisionalApplication No. 61/748,891, entitled “OBFUSCATING AN ENCRYPTION KEY IN ADISPERSED STORAGE NETWORK”, filed Jan. 4, 2013, all of which are herebyincorporated herein by reference in their entirety and made part of thepresent U.S. Utility patent application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of an embodiment of a dataobfuscation system in accordance with the present invention;

FIG. 40B is a schematic block diagram of an embodiment of adeterministic function module in accordance with the present invention;

FIG. 40C is a schematic block diagram of another embodiment of adeterministic function module in accordance with the present invention;

FIG. 40D is a schematic block diagram of another embodiment of adeterministic function module in accordance with the present invention;

FIG. 40E is a flowchart illustrating an example of obfuscating data inaccordance with the present invention;

FIG. 40F is a schematic block diagram of an embodiment of a datade-obfuscation system in accordance with the present invention;

FIG. 40G is a flowchart illustrating an example of de-obfuscating datain accordance with the present invention;

FIG. 41A is a schematic block diagram of an embodiment of a dispersedstorage system in accordance with the present invention;

FIG. 41B is a flowchart illustrating an example of storing a queue entryin accordance with the present invention;

FIG. 42A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention;

FIG. 42B is a flowchart illustrating an example of accessing data inaccordance with the present invention;

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention;

FIG. 43B is a flowchart illustrating an example of migrating data inaccordance with the present invention;

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention;

FIG. 44B is a flowchart illustrating an example of accessing migratingdata in accordance with the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention;

FIG. 45B is a flowchart illustrating an example of generating arebuilding task queue entry in accordance with the present invention;

FIG. 46 is a flowchart illustrating another example of generating arebuilding task queue entry in accordance with the present invention;

FIGS. 47A-B are schematic block diagrams of embodiments of a dispersedstorage network in accordance with the present invention;

FIG. 47C is a diagram illustrating an example of a dispersed storage(DS) parameters table in accordance with the present invention;

FIG. 47D is a diagram illustrating an example of a storage compliancetable in accordance with the present invention;

FIGS. 47E, 47F, 47G and 47H are schematic block diagrams of moreembodiments of a dispersed storage network in accordance with thepresent invention;

FIG. 47I is a flowchart illustrating an achieving storage compliance inaccordance with the present invention;

FIG. 48A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention;

FIG. 48B is a flowchart illustrating an example of deleting data inaccordance with the present invention;

FIG. 49A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention; and

FIG. 49B is a flowchart illustrating another example of accessing datain accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interface 30supports a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26 ), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g., or dispersed storage errorcoding parameters) include data segmenting information (e.g., how manysegments data (e.g., a file, a group of files, a data block, etc.) isdivided into), segment security information (e.g., per segmentencryption, compression, integrity checksum, etc.), error codinginformation (e.g., pillar width, decode threshold, read threshold, writethreshold, etc.), slicing information (e.g., the number of encoded dataslices that will be created for each data segment); and slice securityinformation (e.g., per encoded data slice encryption, compression,integrity checksum, etc.).

The DSTN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19 ).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39 . With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1 . Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1 ), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1 ), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1 . For example, the outboundDST processing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1.

The DST execution units 36 send their respective retrieved slices 100 tothe inbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the grouping selector modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phrase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7 . In this example, data segment 1 includes 3 rows with eachrow being treated as one word for encoding. As such, data segment 1includes three words for encoding: word 1 including data blocks d1 andd2, word 2 including data blocks d16 and d17, and word 3 including datablocks d31 and d32. Each of data segments 2-7 includes three words whereeach word includes two data blocks. Data segment 8 includes three wordswhere each word includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the first set of encoded data slices include error correctiondata based on the first-third words of the first data segment. With suchan encoding and slicing scheme, retrieving any three of the five encodeddata slices allows the data segment to be accurately reconstructed.

The encoding and slicing of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selector module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selector module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selector module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selector module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selector module 114 creates a fourth slice grouping for DSTexecution unit #4, which includes fourth encoded slices of each of thesets of encoded slices. As such, the fourth DST execution unit receivesencoded data slices corresponding to first error encoding information(e.g., encoded data slices of error coding (EC) data). The groupingselector module 114 further creates a fifth slice grouping for DSTexecution unit #5, which includes fifth encoded slices of each of thesets of encoded slices. As such, the fifth DST execution unit receivesencoded data slices corresponding to second error encoding information.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9 ), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_3) is sent to the fourth DST execution unit; the fourth slice groupingof the second data partition (e.g., slice group 2_4, which includesfirst error coding information) is sent to the fifth DST execution unit;and the fifth slice grouping of the second data partition (e.g., slicegroup 2_5, which includes second error coding information) is sent tothe first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions. FIG. 11 is a schematicblock diagram of an embodiment of a DST (distributed storage and/ortask) execution unit that includes an interface 169, a controller 86,memory 88, one or more DT (distributed task) execution modules 90, and aDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9 . The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 in thememory 88. For example, when the partial task 98 includes a retrievalrequest, the controller 86 outputs the memory control 174 to the memory88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step of executing the task in accordance with the taskcontrol information 176, the DT execution module 90 retrieves theencoded slices from memory 88. The DT execution module 90 thenreconstructs contiguous data blocks of a data partition. As shown forthis example, reconstructed contiguous data blocks of data partition 1include data blocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieved slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9 .Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6 ) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8 , an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10 .

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23 .The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24 .

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21 . TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a ReedSolomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selector module organizes the sets of encoded dataslices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selector module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selector module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6 ) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19 .

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39 . In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distribution module's location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39 .

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28 . The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task⇔sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_1_AA, and DS parameters of 3/5; SEG_1;and SLC_1. In this example, the addressing information may be a virtualaddress corresponding to the virtual address of the first storage word(e.g., one or more bytes) of the data and information on how tocalculate the other addresses, may be a range of virtual addresses forthe storage words of the data, physical addresses of the first storageword or the storage words of the data, may be a list of slice names ofthe encoded data slices of the data, etc. The DS parameters may includeidentity of an error encoding scheme, decode threshold/pillar width(e.g., 3/5 for the first data entry), segment security information(e.g., SEG_1), per slice security information (e.g., SLC_1), and/or anyother information regarding how the data was encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_2_XY, and DSparameters of 3/5; SEG 2; and SLC_2. In this example, the addressinginformation may be a virtual address corresponding to the virtualaddress of the first storage word (e.g., one or more bytes) of the taskand information on how to calculate the other addresses, may be a rangeof virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., 3/5 for the first data entry),segment security information (e.g., SEG_2), per slice securityinformation (e.g., SLC_2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task ⇔sub-task mapping information table 246 includes a task field256 and a sub-task field 258. The task field 256 identifies a taskstored in the memory of a distributed storage and task network (DSTN)module and the corresponding sub-task fields 258 indicates whether thetask includes sub-tasks and, if so, how many and if any of the sub-tasksare ordered. In this example, the task ⇔sub-task mapping informationtable 246 includes an entry for each task stored in memory of the DSTNmodule (e.g., task 1 through task k). In particular, this exampleindicates that task 1 includes 7 sub-tasks; task 2 does not includesub-tasks, and task k includes r number of sub-tasks (where r is aninteger greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_1, 1_2, and 1_3). The DT execution capabilities field 280includes identity of the capabilities of the corresponding DT executionunit. For example, DT execution module 1_1 includes capabilities X,where X includes one or more of MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.), and/or any information germane toexecuting one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_1—identifynon-words (non-ordered); task 1_2—identify unique words (non-ordered);task 1_3—translate (non-ordered); task 1_4—translate back (ordered aftertask 1_3); task 1_5—compare to ID errors (ordered after task 1-4); task1_6—determine non-word translation errors (ordered after task 1_5 and1_1); and task 1_7—determine correct translations (ordered after 1_5 and1_2). The sub-task further indicates whether they are an ordered task(i.e., are dependent on the outcome of another task) or non-order (i.e.,are independent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_1 translate; andtask 3_2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases 288. The translated data 282 istranslated back 308 (e.g., sub-task 1_4) into the language of theoriginal data to produce re-translated data 284. These two tasks aredependent on the translate task (e.g., task 1_3) and thus must beordered after the translation task, which may be in a pipelined orderingor a serial ordering. The re-translated data 284 is then compared 310with the original data 92 to find words and/or phrases that did nottranslate (one way and/or the other) properly to produce a list ofincorrectly translated words 294. As such, the comparing task (e.g.,sub-task 1_5) 310 is ordered after the translation 306 andre-translation tasks 308 (e.g., sub-tasks 1_3 and 1_4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 . As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29 , the respective data/task has DSparameters of 3/5 for their decode threshold/pillar width; hencespanning the memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30 . The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30 , where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done by the DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_1 (e.g., identify non-words on the data) has no task ordering (i.e.,is independent of the results of other sub-tasks), is to be performed ondata partitions 2_1 through 2_z by DT execution modules 1_1, 2_1, 3_1,4_1, and 5_1. For instance, DT execution modules 1_1, 2_1, 3_1, 4_1, and5_1 search for non-words in data partitions 2_1 through 2_z to producetask 1_1 intermediate results (R1-1, which is a list of non-words). Task1_2 (e.g., identify unique words) has similar task execution informationas task 1_1 to produce task 1_2 intermediate results (R1-2, which is thelist of unique words).

Task 1_3 (e.g., translate) includes task execution information as beingnon-ordered (i.e., is independent), having DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1 through 2_4 andhaving DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2 translate datapartitions 2_5 through 2_z to produce task 1_3 intermediate results(R1-3, which is the translated data). In this example, the datapartitions are grouped, where different sets of DT execution modulesperform a distributed sub-task (or task) on each data partition group,which allows for further parallel processing.

Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to beexecuted on task 1_3's intermediate result (e.g., R1-3_1) (e.g., thetranslated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 areallocated to translate back task 1_3 intermediate result partitionsR1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2, 6_1, 7_1, and7_2 are allocated to translate back task 1_3 intermediate resultpartitions R1-3_5 through R1-3_z to produce task 1-4 intermediateresults (R1-4, which is the translated back data).

Task 1_5 (e.g., compare data and translated data to identify translationerrors) is ordered after task 1_4 and is to be executed on task 1_4'sintermediate results (R4-1) and on the data. DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 are allocated to compare the data partitions (2_1through 2_z) with partitions of task 1-4 intermediate results partitionsR1-4_1 through R1-4_z to produce task 1_5 intermediate results (R1-5,which is the list words translated incorrectly).

Task 1_6 (e.g., determine non-word translation errors) is ordered aftertasks 1_1 and 1_5 and is to be executed on tasks 1_1's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_1, 2_1,3_1, 4_1, and 5_1 are allocated to compare the partitions of task 1_1intermediate results (R1-1_1 through R1-1_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_6 intermediate results (R1-6, which is the list translation errors dueto non-words).

Task 1_7 (e.g., determine words correctly translated) is ordered aftertasks 1_2 and 1_5 and is to be executed on tasks 1_2's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2 are allocated to compare the partitions of task 1_2intermediate results (R1-2_1 through R1-2_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_7 intermediate results (R1-7, which is the list of correctlytranslated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_1 through 2_z by DT execution modules3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT execution modules 3_1,4_1, 5_1, 6_1, and 7_1 search for specific words and/or phrases in datapartitions 2_1 through 2_z to produce task 2 intermediate results (R2,which is a list of specific words and/or phrases). Task 3_2 (e.g., findspecific translated words and/or phrases) is ordered after task 1_3(e.g., translate) is to be performed on partitions R1-3_1 through R1-3_zby DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2. For instance, DTexecution modules 1_2, 2_2, 3_2, 4_2, and 5_2 search for specifictranslated words and/or phrases in the partitions of the translated data(R1-3_1 through R1-3_z) to produce task 3_2 intermediate results (R3-2,which is a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_1), DST unit 1 isresponsible for overseeing execution of the task 1_1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30 . In FIG.33 , the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation information ofFIG. 32 ) executes task 1_1 to produce a first partial result 102 ofnon-words found in the first data partition. The second set of DTexecution modules (e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DSTallocation information of FIG. 32 ) executes task 1_1 to produce asecond partial result 102 of non-words found in the second datapartition. The sets of DT execution modules (as per the DST allocationinformation) perform task 1_1 on the data partitions until the “z” setof DT execution modules performs task 1_1 on the “zth” data partition toproduce a “zth” partial result 102 of non-words found in the “zth” datapartition.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 1 is assigned to process the first through “zth” partialresults to produce the first intermediate result (R1-1), which is a listof non-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g., R1-1_1through R1-1_m). If the first intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34 , the DSTN module is performing task 1_2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_2 inaccordance with the DST allocation information. From data partition todata partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 1 is assigned to process the first through “zth” partialresults 102 of task 1_2 to produce the second intermediate result(R1-2), which is a list of unique words found in the data 92. Theprocessing module of DST execution 1 is engaged to aggregate the firstthrough “zth” partial results of unique words to produce the secondintermediate result. The processing module stores the secondintermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g., R1-2_1through R1-2_m). If the second intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35 , the DSTN module is performing task 1_3 (e.g., translate) onthe data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task 1_1if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_3 inaccordance with the DST allocation information (e.g., DT executionmodules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1through 2_4 and DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2translate data partitions 2_5 through 2_z). For the data partitions, theallocated set of DT execution modules 90 executes task 1_3 to producepartial results 102 (e.g., 1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 2 is assigned to process the first through “zth” partialresults of task 1_3 to produce the third intermediate result (R1-3),which is translated data. The processing module of DST execution 2 isengaged to aggregate the first through “zth” partial results oftranslated data to produce the third intermediate result. The processingmodule stores the third intermediate result as non-DS error encoded datain the scratchpad memory or in another section of memory of DSTexecution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g., R1-3_1through R1-3_y). For each partition of the third intermediate result,the DST client module uses the DS error encoding parameters of the data(e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35 , the DSTN module is performing task 1_4(e.g., retranslate) on the translated data of the third intermediateresult. To begin, the DSTN module accesses the translated data (from thescratchpad memory or from the intermediate result memory and decodes it)and partitions it into a plurality of partitions in accordance with theDST allocation information. For each partition of the third intermediateresult, the DSTN identifies a set of its DT execution modules 90 toperform task 1_4 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated totranslate back partitions R1-3_1 through R1-3_4 and DT execution modules1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back partitionsR1-3_5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 3 is assigned to process the first through “zth” partialresults of task 1_4 to produce the fourth intermediate result (R1-4),which is retranslated data. The processing module of DST execution 3 isengaged to aggregate the first through “zth” partial results ofretranslated data to produce the fourth intermediate result. Theprocessing module stores the fourth intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36 , a distributed storage and task network (DSTN) module isperforming task 1_5 (e.g., compare) on data 92 and retranslated data ofFIG. 35 . To begin, the DSTN module accesses the data 92 and partitionsit into a plurality of partitions in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. The DSTN module also accesses the retranslateddata from the scratchpad memory, or from the intermediate result memoryand decodes it, and partitions it into a plurality of partitions inaccordance with the DST allocation information. The number of partitionsof the retranslated data corresponds to the number of partitions of thedata.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_5 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_5 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 1 is assigned to process the first through “zth” partialresults of task 1_5 to produce the fifth intermediate result (R1-5),which is the list of incorrectly translated words and/or phrases. Inparticular, the processing module of DST execution 1 is engaged toaggregate the first through “zth” partial results of the list ofincorrectly translated words and/or phrases to produce the fifthintermediate result. The processing module stores the fifth intermediateresult as non-DS error encoded data in the scratchpad memory or inanother section of memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_1 through R1-5_z). Foreach partition of the fifth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36 , the DSTN module is performing task 1_6(e.g., translation errors due to non-words) on the list of incorrectlytranslated words and/or phrases (e.g., the fifth intermediate resultR1-5) and the list of non-words (e.g., the first intermediate resultR1-1). To begin, the DSTN module accesses the lists and partitions theminto a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_6 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_6 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases due to non-words.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 2 is assigned to process the first through “zth” partialresults of task 1_6 to produce the sixth intermediate result (R1-6),which is the list of incorrectly translated words and/or phrases due tonon-words. In particular, the processing module of DST execution 2 isengaged to aggregate the first through “zth” partial results of the listof incorrectly translated words and/or phrases due to non-words toproduce the sixth intermediate result. The processing module stores thesixth intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_1 through R1-6_z). Foreach partition of the sixth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36 , the DSTN module is performingtask 1_7 (e.g., correctly translated words and/or phrases) on the listof incorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_7 in accordance with the DST allocation information(e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2). For each pairof partitions, the allocated set of DT execution modules executes task1_7 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 3 is assigned to process the first through “zth” partialresults of task 1_7 to produce the seventh intermediate result (R1-7),which is the list of correctly translated words and/or phrases. Inparticular, the processing module of DST execution 3 is engaged toaggregate the first through “zth” partial results of the list ofcorrectly translated words and/or phrases to produce the seventhintermediate result. The processing module stores the seventhintermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37 , the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 7 is assigned to process the first through “zth” partialresults of task 2 to produce task 2 intermediate result (R2), which is alist of specific words and/or phrases found in the data. The processingmodule of DST execution 7 is engaged to aggregate the first through“zth” partial results of specific words and/or phrases to produce thetask 2 intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terra-Byte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38 , the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32 , DSTexecution unit 5 is assigned to process the first through “zth” partialresults of task 3 to produce task 3 intermediate result (R3), which is alist of specific translated words and/or phrases found in the translateddata. In particular, the processing module of DST execution 5 is engagedto aggregate the first through “zth” partial results of specifictranslated words and/or phrases to produce the task 3 intermediateresult. The processing module stores the task 3 intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30 . In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of an embodiment of a dataobfuscation system that includes an encryptor 350, a deterministicfunction 352, a key masking function 354, a combiner 356, an encoder358, and a dispersed storage network (DSN) memory 360. The DSN memory360 includes at least one set of storage units. The encryptor 350encrypts data 362 using an encryption key 364 to produce encrypted data366 in accordance with an encryption function. The key 364 is obtainedfrom at least one of a local memory, received in a message, generatedbased on a random number, and deterministically generated from at leastpart of the data 362. The deterministic function 352 performs adeterministic function on the encrypted data 366 using a password 368 toproduce transformed data 370, where the transformed data 370 has a samenumber of bits as the encryption key 364. The password 368 includes anyprivate sequence of information (e.g., alphanumeric digits). Thepassword 368 may be obtained by one or more of a lookup, receiving froma user interface input, retrieving from the DSN memory, and performing auser device query. The deterministic function 352 may be based on one ormore of a hashing function, a hash based message authentication codefunction, a mask generating function, a concatenation function, a spongefunction, and a key generation function. The method of operation of thedeterministic function is described in greater detail with reference toFIGS. 40B-40D.

The key masking function 354 masks the key 364 using the transformeddata 370 to produce a masked key 372, where the masked key 372 includesthe same number of bits as the key 364. The masking may include at leastone of a logical mathematical function, a deterministic function, and anencryption function. For example, the masking includes performing anexclusiveOR (XOR) logical function on the key 364 and the transformeddata 370 to produce the masked key 372. The combiner 356 combines theencrypted data 366 and the masked key 372 to produce a secure package374. The combining may include at least one of pre-appending,post-appending, inserting, and interleaving. The encoder 358 performs adispersed storage error coding function on the secure package 374 toproduce one or more sets of slices 376 in accordance with dispersedstorage error coding function parameters for storage in the DSN memory360.

FIG. 40B is a schematic block diagram of an embodiment of adeterministic function module 352 that includes a hash based messageauthentication code function module (HMAC) 378. The HMAC function 378performs a hash based message authentication code function on encrypteddata 366 using a password 368 as a key of the HMAC to producetransformed data 370.

FIG. 40C is a schematic block diagram of another embodiment of adeterministic function module 352 that includes a concatenation function380 and a hashing function 382. The concatenation function 380concatenates encrypted data 366 and a password 368 to produce anintermediate result. For example, the concatenation function 380combines the encrypted data 366 and the password 368 by appending thepassword 368 to the encrypted data 366 to produce the intermediateresult. The hashing function 382 performs a deterministic hashingalgorithm on the intermediate result to produce transformed data 370.Alternatively, a mask generating function may be utilized as the hashingfunction 382.

FIG. 40D is a schematic block diagram of another embodiment of adeterministic function module 352 that includes a hashing function 382,a key generation function 384, and a sub-key masking function 386. Thehashing function 382 performs a deterministic hashing algorithm onencrypted data 366 to produce a hash of the encrypted data.Alternatively, a mask generating function may be utilized as the hashingfunction 382. The key generation function 384 generates an intermediatekey based on a password 368, where the intermediate key includes a samenumber of bits as the encryption key utilized in the system of FIG. 40A.The key generation function 384 includes at least one of a keyderivation function, a hashing function, and a mask generating function.The sub-key masking function 386 may include at least one of a logicalmathematical function, a deterministic function, and an encryptionfunction. For example, the sub-key masking includes performing anexclusiveOR (XOR) logical function on the intermediate key and the hashof the encrypted data to produce transformed data 370.

FIG. 40E is a flowchart illustrating an example of obfuscating data. Themethod begins at step 388 where a processing module (e.g., of adispersed storage processing module) encrypts data using a key toproduce encrypted data. The method continues at step 390 where theprocessing module performs a deterministic function on the encrypteddata and a password to produce transformed data. The method continues atstep 392 where the processing module masks the key utilizing a maskingfunction based on the transformed data to produce a masked key. Forexample, the processing module performs an exclusiveOR function on thekey and the transformed data to produce the masked key.

The method continues at step 394 where the processing module combines(e.g., pre-append, post-append, insert, interleave, etc.) the encrypteddata and the masked key to produce a secure package. The methodcontinues at step 396 where the processing module encodes the securepackage to produce a set of encoded data slices using a dispersedstorage error coding function. The method continues at step 398 wherethe processing module outputs the set of encoded data slices. Forexample, the processing module outputs the set of encoded data slices toa dispersed storage network memory for storage therein. As anotherexample, the processing module outputs the set of encoded data slices toa communication network for transmission to one or more receivingentities.

FIG. 40F is a schematic block diagram of an embodiment of a datade-obfuscation system that includes a dispersed storage network (DSN)memory 360, a decoder 400, a de-combiner 402, a deterministic function352, a key de-masking function 404, and a decryptor 406. The decoder 400obtains (e.g., retrieves, receives) one or more sets of encoded dataslices 376 from the DSN memory 360. The decoder 400 decodes the one ormore sets of encoded data slices 376 using a dispersed storage errorcoding function in accordance with dispersed storage error codingfunction parameters to reproduce at least one secure package 374. Forexample, the decoder decodes a first set of encoded data slices toproduce a first secure package.

For each secure package 374, the de-combiner 402 de-combines the securepackage 374 to reproduce encrypted data 366 and a masked key 372. Thede-combining includes at least one of de-appending, un-inserting, andde-interleaving in accordance with a de-combining scheme. Thedeterministic function 352 performs a deterministic function on theencrypted data 366 using a password 368 to reproduce transformed data370, where the transformed data 370 has a same number of bits as arecovered encryption key 364. The password 368 includes any privatesequence of information and is substantially identical to a password 368of a complementary encoder.

The key de-masking function 404 de-masks the masked key 372 using thetransformed data 370 to produce the recovered key 364, where therecovered key 364 includes a same number of bits as the masked key 372.The de-masking may include at least one of a logical mathematicalfunction, a deterministic function, and an encryption function. Forexample, the de-masking includes performing an exclusiveOR (XOR) logicalfunction on the masked key and the transformed data to produce therecovered key. The decryptor 406 decrypts the encrypted data 366 usingthe recovered key 364 to reproduce data 362 in accordance with adecryption function.

FIG. 40G is a flowchart illustrating an example of de-obfuscating data,which includes similar steps to FIG. 40E. The method begins at step 408where a processing module (e.g., of a dispersed storage processingmodule) obtains a set of encoded data slices. The obtaining includes atleast one of retrieving and receiving. For example, the processingmodule receives the set of encoded data slices from a dispersed storagenetwork memory. As another example, the processing module receives theset of encoded data slices from a communication network. The methodcontinues at step 410 where the processing module decodes the set ofencoded data slices to reproduce a secure package using a dispersedstorage error coding function and in accordance with dispersed storageerror coding function parameters.

The method continues at step 412 where the processing module de-combinesthe secure package to produce encrypted data and a masked key. Forexample, the processing module partitions the secure package to producethe encrypted data and the masked key in accordance with a partitioningscheme. The method continues with step 390 of FIG. 40E where theprocessing module performs a deterministic function on encrypted dataand a password to reproduce transformed data. The method continues atstep 414 where the processing module de-masks the masked key utilizing ade-masking function based on the transformed data to reproduce arecovered key. For example, the processing module performs anexclusiveOR function on the masked key and the transformed data toproduce the recovered key. The method continues at step 416 where theprocessing module decrypts the encrypted data using the recovered key toreproduce data.

FIG. 41A is a schematic block diagram of an embodiment of a dispersedstorage system that includes a client module 420, a dispersed storage(DS) processing module 422, and a DS unit set 424. The DS unit set 424includes a set of DS units 426 utilized to access slices stored in theset of DS units 426. The DS unit 426 may be implemented using thedistribute storage and task (DST) execution unit 36 of FIG. 1 . Theclient module 420 may be implemented utilizing at least one of a userdevice, a distributed storage and task (DST) client module, a DSTprocessing unit, a DST execution unit, and a DS processing unit. The DSprocessing module 422 may be implemented utilizing at least one of a DSTclient module, a DST processing unit, a DS processing unit, a userdevice, a DST execution unit, and a DS unit. The system is operable tofacilitate storage of one or more queue entries of a queue in the DSunit set 424.

In an example of operation, the client module 420 generates a writequeue entry request 428 where the write queue entry request 428 includesone or more of a queue entry, a queue name, and an entry number. Theclient module 420 may utilize the entry number to facilitate ordering oftwo or more queue entries. The client module 420 outputs the write queueentry request 428 to the DS processing module 422. The DS processingmodule 422 encodes the queue entry using a dispersed storage errorcoding function to produce a set of queue entry slices 432. For each DSunit 426 of the DS unit set 424, the DS processing module 422 generatesa write request 430 and outputs the write request 430 to the DS unit 426to facilitate storage of the queue entry slices by the DS unit set 424.

The write request 430 includes one or more of a queue entry slice 432 ofthe set of queue entry slices and a slice name 434 corresponding to thequeue entry slice 432. The DS processing module 422 generates the slicename 434 based on the write queue entry request 428. The slice name 434includes a slice index field 436 and a vault source name field 438. Theslice index field 436 includes a slice index entry that corresponds to apillar number of a set of pillar numbers associated with a pillar widthdispersal parameter utilized in the dispersed storage error codingfunction. The vault source name field 438 includes a queue vaultidentifier (ID) field 440 and a queue entry ID field 442. The queuevault ID 440 includes an identifier of a vault of the dispersed storagesystem associated with the queue (e.g., a vault associated with theclient module 420). The DS processing module 422 generates a queue vaultID entry for the queue vault ID field 440 by a one or more of adispersed storage network registry lookup based on an identifier of arequesting entity associated with the write queue entry request 428,receiving the queue vault ID, and generating a new queue vault ID when anew queue name is requested (e.g., not previously utilized in thedispersed storage network).

The queue entry ID field 442 includes a queue name field 444, a DSprocessing module ID field 446, a client ID field 448, and a timestampfield 450. The DS processing module 422 generates a queue name entry forthe queue name field 444 based on the queue name of the write queueentry request 428. The DS processing module 422 generates a DSprocessing module ID entry for the DS processing module ID field 446 asan identifier associated with the DS processing module 422 by at leastone of a lookup, receiving, and generating when the ID has not beenassigned so far. The DS processing module 422 generates a client IDentry for the client ID field 448 as an identifier associated with theclient module 420 (e.g., requesting entity) by at least one of a lookup,extracting from the write queue entry request 428, initiating a query,and receiving. The DS processing module 422 generates a timestamp entryfor the timestamp field 450 as at least one of a current timestamp, theentry number of the write queue entry request 428 (e.g., when provided),and a combination of the current timestamp and the entry number. In animplementation example, the slice name is 48 bytes, the queue entry IDfield is 24 bytes, the queue name field is 8 bytes, the DS processingmodule ID is 4 bytes, the client ID field is 4 bytes, and the timestampfield is 8 bytes.

FIG. 41B is a flowchart illustrating an example of storing a queueentry. The method begins at step 452 where a processing module (e.g., ofa dispersed storage (DS) processing module) receives a write queue entryrequest. The request includes one or more of a requesting entityidentifier (ID), a queue entry, a queue name, and an entry number. Themethod continues at step 454 where the processing module identifies aqueue vault ID. The identifying may be based on one or more of therequesting entity ID, the queue name, and a look up. For example, theprocessing module accesses a queue directory utilizing the queue name toidentify the queue vault ID.

The method continues at step 456 where the processing module identifiesa DS processing module ID associated with processing of the write queueentry request. The identifying may be based on one or more of generatinga new ID, extracting from the request, a lookup, initiating a query, andreceiving the identifier. The method continues at step 458 where theprocessing module identifies a client ID associated with the requestingentity. The identifying may be based on one or more of extracting fromthe request, a lookup, initiating a query, and receiving the identifier.The method continues at step 460 where the processing module generates atimestamp.

The generating includes at least one of obtaining a real-time time valueand utilizing the entry number of the write queue entry request whenprovided. The method continues at step 462 where the processing modulegenerates a set of slice names based on one or more of the queue vaultID, the DS processing module ID, the client ID, and the timestamp. Forexample, the processing module generates a slice name of the set ofslice names to include a slice index corresponding to a slice to beassociated with the slice name, the queue vault ID, the queue name ofthe write queue entry request, the DS processing module ID, the clientID, and the timestamp as depicted in FIG. 41A.

The method continues at step 464 where the processing module encodes thequeue entry of the write queue entry request using a dispersed storageerror coding function to produce a set of queue entry slices. The methodcontinues at step 466 where the processing module generates a set ofwrite requests that includes the set of queue entry slices and the setof slice names. The method continues at step 468 where the processingmodule outputs the set of write requests to a set of DS units tofacilitate storage of the set of queue entry slices.

FIG. 42A is a schematic block diagram of another embodiment of adispersed storage system that includes a dispersed storage (DS)processing module 422 and a DS unit 426. The DS unit 426 includes acontroller 470, a queue memory 472, and a main memory 474. The queuememory 472 and the main memory 474 may be implemented utilizing one ormore memory devices. Each memory device of the one or more memorydevices may be implemented utilizing at least one of solid-state memorydevice, a magnetic disk drive, and an optical disk drive. The queuememory 472 may be implemented with memory technology to provide improvedperformance (e.g., lower access latency, higher bandwidth) as comparedto the main memory 474. For example, the queue memory 472 is implementedutilizing dynamic random access memory (DRAM) to be utilized for storageof small sets of small encoded queue slices and/or lock slices. The mainmemory 474 may be implemented with other memory technology to provideimproved cost (e.g., lowered cost) as compared to the queue memory. Forexample, the main memory 474 is implemented utilizing magnetic diskmemory technology to be utilized for storage of large sets of largeencoded data slices.

The DS processing module 422 generates a write request 430 that includesa queue entry slice 432 and a slice name 434 for outputting to the DSunit 426. The controller 470 receives the write request 430 anddetermines whether to utilize queue memory 472 or main memory 474 forstorage of the queue entry slice 432 of the write request 430. Thedetermining may be based on one or more of a queue entry sliceidentifier, a requesting entity identifier, and matching the slice name434 to a queue entry slice name address range. When the controller 470determines to utilize the queue memory 472, the controller 470 storesthe queue entry slice 432 in the queue memory 472. The method ofoperation is discussed in greater detail with reference to FIG. 42B.

FIG. 42B is a flowchart illustrating an example of accessing data. Themethod begins at step 476 where a processing module (e.g., of adispersed storage (DS) unit) receives a slice access request. The methodcontinues at step 478 where the processing module identifies a slicetype to produce an identified slice type. The slice type includes atleast one of a queue entry slice, a lock slice, an index node slice, anda data node. The identifying may be based on one or more of mapping aslice name of the slice access request to an address range associatedwith a slice type of a plurality of slice types, extracting a slice typeindicator from the request, and analyzing an encoded data slice of therequest.

The method continues at step 480 where the processing module selects amemory type based on the identified slice type to produce a selectedmemory type. For example, the processing module selects a queue memorywhen the identified slice type is a queue entry slice. As anotherexample, the processing module selects a main memory when the identifiedslice type is not a queue entry slice and not a lock entry slice. Themethod continues at step 482 where the processing module selects amemory based on the selected memory type to produce a selected memory.The selecting may be based on one or more of available memory capacity,a slice size indicator, a memory reliability indicator, and a memorysize threshold level. For example, the processing module selects a tenthqueue memory device of the queue memory when the tenth queue memory hasavailable memory capacity greater than the slice size of a queue entryslice for storage and a first through a ninth queue memory devices arefull for a write request. Alternatively, the processing module mayselect another memory type to identify a memory of the other memory typewhen all memory devices of the selected memory type are unavailable fora request. For example, the processing module selects a second mainmemory device of the main memory when all queue memory devices of thequeue memory are full and the slice type is a queue entry slice for awrite request.

The method continues at step 484 where the processing module facilitatesthe slice access request utilizing the selected memory. For example,when the slice access request is a write request, the processing modulestores a received slice of the request in the selected memory. Asanother example, when the slice access request is a read request, theprocessing module retrieves a slice from the selected memory and outputsthe retrieved slice to a requesting entity.

In various embodiments, a method is presented for execution by aprocessing system that includes a processing circuit. A method includesreceiving a write request to store a data object; identifying objectparameters associated with the data object; selecting a memory typebased on the identified object parameters; selecting a selected memorybased on the memory type; and facilitating storage of the data object inthe selected memory, wherein the data object is dispersed error encoded.

In various embodiments, the object parameters include a size indicatorassociated with the data object, such as data segment is dispersed errorencoded into a plurality of data slices. The object parameters can alsoinclude temporary storage identifier associated with the data object,that for example, a identifies a data object for queue entry. The memorytype can include a temporary storage, such as a queue memory device. Thetemporary storage can be implemented via a solid state memory devicethat has a lower latency and/or a lower access latency compared to othermemory devices associated with at least one other memory type. Thememory type can further include a main memory space that is implementedvia a random access memory space.

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage system that includes a legacy data storage system 486,a dispersed storage (DS) processing module 422, and a DS unit set 424.The DS unit set 424 includes a set of DS units 426 utilized to accessslices stored in the set of DS units 426. The legacy data storage system486 may be implemented utilizing any one of a variety ofindustry-standard storage technologies. The DS processing module 422 maybe implemented utilizing at least one of a distributed storage and task(DST) client module, a DST processing unit, a DS processing unit, a userdevice, a DST execution unit, and a DS unit. The system is operable tofacilitate migration of data from the legacy data storage system 486 tothe DS unit set 424.

The legacy data storage system 486 provides object information 488 anddata objects 492 to the DS processing module 422. The object information488 includes one or more of object names of the data objects 492 storedin the legacy data storage system 486 and object sizes corresponding tothe data objects 492. The processing module 422 receives the objectinformation 488 and the data objects 492 from the legacy storage system486 and stores at least some of the object information 488 in adispersed index in the DS unit set 424. The dispersed index includes aplurality of index nodes and a plurality of leaf nodes where each of theplurality of index nodes and the plurality of leaf nodes are stored as aset of encoded index slices 490 in the DS unit set 424. Each leaf nodeof the dispersed index includes at least one entry corresponding to adata object 492 stored in the DS unit set 424, where the entry includesan index key associated with the data object 492. The plurality of indexnodes provide a hierarchical structure to the dispersed index toidentify a leaf node associated with the data object 492 based on theindex key (e.g., searching through the hierarchy of index nodes based oncomparing the index key to minimum index keys of each index node).

The storing in the dispersed index includes generating the index keyassociated with the corresponding data object 492 for each portion ofthe object information 488 and adding/modifying an entry of thedispersed index to include one or more of the index key, the objectname, the object size, and an index entry state. The index entry stateincludes an indication of a migration state with regards to migratingthe data object 492 from the legacy data storage system 486 to the DSunit set 424. The indication of migration state includes one of to bemoved, moving, and moved. For example, the indication of migration stateindicates to be moved when the data object 492 has been identified formigration from the legacy data storage system 486 to the DS unit set 424when the moving has not been initiated. The DS processing module 422initializes the index entry state to indicate to be moved. Theinitializing includes encoding a corresponding leaf node to produce aset of index slices 490 and outputting the set of index slices 490 tothe DS unit set 424.

The DS processing module 422 encodes the data object 492 to produce dataslices 494 and outputs the data slices 494 to the DS unit set 424 forstorage. The DS processing module 422 updates the index entry state forthe data object 492 to indicate the moving state (e.g., and not the tobe moved state). When storage in the DS unit set 424 of a thresholdnumber (e.g., a write threshold) of data slices 494 has been confirmed,the DS processing module 422 issues a delete request 496 to the legacydata storage system to delete the data object 492 from the legacy datastorage system 486. When deletion of the data object 492 from the legacydata storage system 486 has been confirmed, the DS processing module 422updates the index entry state for the data object 492 to indicate themoved state. The DS processing module 422 detects confirmation ofdeletion of the data object from the legacy data storage system 486 whenreceiving a favorable delete response 498 from the legacy data storagesystem 486 with regards to the data object 492. The method of operationis discussed in greater detail with reference to FIG. 43B.

FIG. 43B is a flowchart illustrating an example of migrating data. Themethod begins at step 500 where a processing module (e.g., a dispersedstorage (DS) processing module) receives object information for a dataobject (e.g., from a legacy data storage system). The receiving mayinclude outputting an object information request, receiving the dataobject, receiving the object information, receiving a migration request,and initiating a query. The method continues at step 502 where theprocessing module stores the object information in a dispersed indexwhere the data object is associated with a to-be-moved index entrystate. The storing includes establishing an index key of the data objectbased on one or more of the data object, a data object size indicator,and a data object identifier of the data object and modifying/updating aleaf node entry of a leaf node corresponding to the data object toinclude the index key, the object information, and an index entry stateto indicate to be moved.

The method continues at step 504 where the processing module encodes thedata object to produce data slices for storage in a set of DS units. Theencoding includes encoding the data object using a dispersed storageerror coding function to produce a plurality of encoded data slices,generating a plurality of slice names corresponding to the plurality ofencoded data slices, generating a plurality of write slice requests thatincludes a plurality of slice names and the plurality of encoded dataslices, and outputting the plurality of write slice requests to the DSunit set.

The method continues at step 506 where the processing module updates thedispersed index to indicate that the index entry state for the dataobject has changed to moving. For example, the processing moduleretrieves the leaf node (e.g., retrieves a set of index slices from theset of DS units, decodes the set of index slices to reproduce the leafnode), updates the index entry state to indicate moving to produce amodified leaf node, and stores the modified leaf node in the set of DSunits (e.g., encodes the leaf node to produce a set of index slices,outputs the set of index slices to the set of DS units for storage).

When storage is confirmed, the method continues at step 508 where theprocessing module outputs a delete data object request to the legacydata storage system. For example, the processing module receives atleast a write threshold number of favorable write slice responses fromthe set of DS units, generates the delete data object request to includethe data object identifier, and outputs the delete data object requestto the legacy data storage system. When deletion of the data object isconfirmed, the method continues at step 510 where the processing moduleupdates the dispersed index to indicate that the index entry state forthe data object has changed to moved. For example, the processing modulereceives a delete data response from the legacy data storage systemindicating that the deletion of the data object is confirmed, retrievesthe leaf node, updates the index entry state to indicate moved toproduce a further modified leaf node, and stores the further modifiedleaf node in the set of DS units.

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage system that includes a legacy data storage system 486,a dispersed storage (DS) processing module 422, and a DS unit set 424.The DS unit set 424 includes a set of DS units 426 utilized to accessslices stored in the set of DS units 426. The legacy data storage system486 may be implemented utilizing any one of a variety ofindustry-standard storage technologies. The DS processing module 422 maybe implemented utilizing at least one of a distributed storage and task(DST) client module, a DST processing unit, a DS processing unit, a userdevice, a DST execution unit, and a DS unit. The system is operable tofacilitate accessing migrating data while the data is being migratedfrom the legacy data storage system 486 to the DS unit set 424.

The DS processing module 422 receives a data access request 512 (e.g.,from a client module, from a user device, from a requesting entity)where the data access request 512 includes at least one of a readrequest, a write request, a delete request, and a list request. The DSprocessing module 422 processes the data access request 512, generates adata access response 514 based on the processing, and outputs the dataaccess response 514 (e.g., to the client module, to the user device, tothe requesting entity).

In an example of processing the data access request 512, the data accessrequest includes the read request such that the DS processing module 422receives the data access request 512 to read a data object. Havingreceived the read requests, the DS processing module 422 accesses adispersed index to identify an index entry state corresponding to thedata object. The accessing includes generating a set of index slicerequests 520 corresponding to a leaf node of the dispersed indexassociated with the data object, outputting the set of index slicerequests 520 to the DS unit set 424, receiving at least a decodethreshold number of index slice responses 522, and decoding the at leastthe decode threshold number of index slice responses 522 to reproducethe leaf node containing the index entry state corresponding to the dataobject. When the state indicates moved, the DS processing module 422retrieves the data object from the DS unit set 424 (e.g., issuing dataslice access requests 524 to the DS unit set 424, receiving data sliceaccess responses 526, and decoding the data slice access responses 526to reproduce the data object). When the state does not indicate moved,the DS processing module 422 retrieves the data object from the legacydata storage system 486 (e.g., issuing a data object request 516 to thelegacy data storage system 486 and receiving a data object response 518that includes the data object).

In another example of processing the data access request 512, the DSprocessing module 422 receives a data access request 512 to writeanother data object. The DS processing module 422 accesses the dispersedindex to identify a dispersed storage network (DSN) address associatedwith storage of the other data object (e.g., retrieves the leaf nodeassociated with the data object to produce the DSN address). The DSprocessing module 422 stores the other data object in the DS unit set424 utilizing the DSN address (e.g., issuing data slice access requests524 that includes slice names based on the DSN address and encoded dataslices produced from encoding the other data object using a dispersedstorage error coding function).

In another example of processing the data access request 512, the DSprocessing module 422 receives a data access request 512 to delete thedata object. The DS processing module 422 accesses the dispersed indexto determine the index entry state corresponding to the data object.When the index entry state indicates moved, the DS processing module 422facilitates deletion of the data object from the DS unit set 424 (e.g.,issuing data slice access requests 524 that includes delete requests tothe DS unit set 424). When the index entry state indicates moving, theDS processing module 422 facilitates deletion of the data object fromthe DS unit set 424 and from the legacy data storage system 486 (e.g.,issuing another data object request 516 that includes a delete dataobject request to the legacy data storage system 486). When the indexentry state indicates to be moved, the DS processing module 422facilitates deletion of the data object from the legacy data storagesystem 486.

In yet another example of processing the data access request 512, the DSprocessing module 422 receives a data access request 512 to list data.The request to list data may include one or more data object namesand/or a DSN address range. The DS processing module 422 accesses thedispersed index to identify one or more DSN addresses associated withthe one or more data object names of the request to list data. The DSprocessing module 422 facilitates issuing a series of data slice accessrequests 524 that includes a series of list requests to the DS unit set424 for slices associated with the one or more DSN addresses and/or theDSN address range. The DS processing module 422 receives data sliceaccess responses 526 that includes list responses. The DS processingmodule 422 issues data object requests 516 to the legacy data storagesystem 486 where the data object requests 516 includes list requests forthe data objects. The DS processing module 422 receives data objectresponses 518 that includes list data object responses. The DSprocessing module 422 aggregates list responses from the legacy datastorage system 486 and the DS unit set 424 to produce a compiled listresponse. The DS processing module 422 issues a data access response 514to a requesting entity, where the data access response 514 includes thecompiled list response.

FIG. 44B is a flowchart illustrating an example of accessing migratingdata. The method begins at step 528 where a processing module (e.g., adispersed storage (DS) processing module) receives a data access requestfrom a requesting entity. When the data access request includes a readrequest, the method branches to step 530. When the data access requestincludes a delete request, the method branches to step 538, when thedata access request includes a list request, the method continues tostep 546.

When the data access request includes the read request, the methodcontinues at step 530 where the processing module determines an indexentry state corresponding to a data object of the request (e.g.,retrieve a leaf node of a dispersed index corresponding to the dataobject to extract the index entry state). When the index entry stateindicates moved, the method continues at step 532 where the processingmodule retrieves the data object from a dispersed storage network (DSN).The retrieving includes generating data slice access requests, receivingdata slice access responses, and decoding data slices of the data sliceaccess responses to reproduce the data object. The method branches tostep 536. When the index entry state does not indicate moved (e.g.,indicates to be moved or moving), the method continues at step 534 wherethe processing module retrieves the data object from the legacy datastorage system. The retrieving includes generating a data objectrequest, outputting the data object request to the legacy data storagesystem, and receiving a data object response from the legacy datastorage system that includes the data object. The method continues atstep 536 where the processing module outputs a data access response thatincludes the data object.

When the data access request includes the delete request, the methodcontinues at step 538 where the processing module determines the indexentry state corresponding to the data object of the request. When theindex entry state indicates to be moved, the method continues at step544 where the processing module deletes the data object from the legacydata storage system (e.g., issues data object requests that includes adelete request to the legacy data storage system). When the index entrystate indicates moved, the method continues at step 540 where theprocessing module deletes the data object from the DSN (e.g., issuesdelete data access slice requests to the DSN). When the index entrystate indicates moving, the method continues at step 542 where theprocessing module deletes the data object from the legacy data storagesystem and the DSN.

When the data access request includes the list request, the methodcontinues at step 546 where the processing module identifies a DSNaddress of the data object (e.g., based on an index lookup using a dataobject identifier of the request). The method continues at step 548where the processing module performs a listing function for the dataobject with the DSN to produce DSN listing results (e.g., issuing listdata slice access requests, receiving list data slice access responsesto produce the DSN listing results). The method continues at step 550where the processing module performs a listing function for the dataobject with the legacy data storage system to produce legacy systemlisting results (e.g., issuing a list data object request to the legacydata storage system, receiving a list data object response to producethe legacy system listing results). The method continues at step 552where the processing module combines the DSN listing results and thelegacy system listing results to produce a compiled list response. Thecombining includes at least one of appending, concatenating,interleaving, and sorting. The method continues at step 554 where theprocessing module outputs a data access response that includes thecompiled list response to the requesting entity.

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage system that includes one or more dispersed storage(DS) unit sets 556 and 424, a scanning module 558, and a rebuildingmodule 560. Each DS unit set 556 and 424 includes a set of DS units 426.In a first embodiment, as illustrated, the one or more DS unit sets 556and 424 are implemented as two separate sets of DS units 426.Alternatively, in another embodiment, the one or more DS unit sets areimplemented as a common DS unit set (e.g., DS unit set 424). Thescanning module 558 and rebuilding module 560 may be implementedutilizing one or more of a user device, a server, a processing module, acomputer, a DS processing unit, a DS processing module, a DS unit, adistributed storage and task (DST) processing unit, a DST processingmodule, a DST client module, and a DST execution unit. For example, thescanning module 558 is implemented in a first DST execution unit and therebuilding module 560 is implemented in a second DST execution unit. Asanother example, the scanning module 558 and the rebuilding module 560are implemented utilizing a common DST execution unit.

The system functions to detect one or more stored slices in error (e.g.,missing and/or corrupted slices that should be stored in one or more DSunits of a first DS unit set 556) and to remedy (e.g., rebuild) the oneor more stored slices in error. The scanning module 558 functions todetect the one or more stored slices in error and the rebuilding modulefunctions 560 to remedy the one or more stored slices in error. Thescanning module 558 communicates identities of the one or more storedslices in error to the rebuilding module 560 by utilizing entries of oneor more dispersed queues stored in the second DS unit set 424.

In an example of operation, the scanning module 558 detects the one ormore stored slices in error and updates the dispersed queue with anentry pertaining to at least one stored slice in error. The scanningmodule 558 functions to detect the one or more stored slices in errorthrough a series of steps. A first step includes generating a set oflist slice requests 562 that include a range of slice names to bescanned associated with the first DS unit set 556. A second stepincludes outputting the set of list slice requests 562 to the first DSunit set 556. A third step includes comparing list slice responses 564from the first DS unit set 556 to identify one or more slice namesassociated with the one or more stored slices in error. For example, thescanning module 558 identifies a slice name that is not listed in a listslice response 564 from a DS unit 426 of the DS unit set 556 when slicenames of a set of slice names that are associated with the slice nameare received via other list slice responses 564 from other DS units 426of the DS unit set 556.

Having identified the one or more stored slices in error, the scanningmodule 558 updates the one or more dispersed queues by sending writequeue entry requests 566 to the second DS unit set 424 through a seriesof steps. A first step includes determining a number of slice errors perset of encoded data slices that includes the slice error. A second stepincludes generating a queue entry that includes one or more of the slicename, the number of slice errors, a rebuilding task indicator, andidentity of the set of slice names that are associated with the slicename (e.g., a source name). A third step includes identifying adispersed queue of the one or more dispersed queues based on the numberof slice errors. A fourth step includes storing the queue entry in theidentified dispersed queue associated with the second DS unit set 424.The storing includes encoding the queue entry to produce a set of entryslices, identifying a rebuilding dispersed queue, generating a set ofentry slice names for the queue entry, generating a set of write slicerequests that includes the set of entry slices and the set of entryslice names, and outputting the set of write slice requests to thesecond DS unit set 424.

With the queue entry in place, the rebuilding module 560 remedies theone or more stored slices in error through a series of steps. A firststep includes retrieving a queue entry from a dispersed queue of the oneor more dispersed queues where the dispersed queue is associated with ahighest number of slice errors. The retrieving includes outputting a setof queue entry requests 568 to the second DS unit set 424 that includesa set of list requests associated with a slice name range of a highestpriority queue entry (e.g., oldest), receiving a set of queue entryresponses that includes a set of list responses, identifying a set ofslice names associated with the queue entry (e.g., lowest slice names ofa range of slice names associated with a first in first out (FIFO)approach), generating and outputting a set of delete read slice requeststhat includes the set of slice names to the second DS unit set 424,receiving at least a decode threshold number of queue entry responses570 that includes entry slices, and decoding the at least a decodethreshold number of entry slices to reproduce the queue entry.

A second step to remedy the one or more stored slices in error includesextracting the slice name of the slice in error from the queue entry. Athird step includes facilitating rebuilding of the slice in error (e.g.,directly rebuilding, issuing a rebuilding request to another rebuildingmodule). When directly rebuilding, the rebuilding module 560 outputs, tothe first DS unit set 556, at least a decode threshold number of readslice requests 572 that includes slice names associated with the slicein error, receives at least a decode threshold number of read sliceresponses 574 that includes slices associated with the slice in error,decodes the slices associated with the slice in error to produce arecovered data segment, and encodes the recovered data segment toproduce a rebuilt slice. A fourth step includes generating andoutputting, to the first DS unit set 556, a write slice request 576 thatincludes the slice name of the slice in error and the rebuilt slice. Afifth step includes receiving a write slice response 578 that includesstatus of writing the rebuilt slice (e.g., succeeded/failed).

When the status of writing the rebuilt slice is favorable (e.g.,succeeded), the rebuilding module 560 generates and outputs, to thesecond DS unit set 424, a set of queue entry requests 568 that includesa set of commit requests associated with the delete read requestspreviously output to the second DS unit set 424 with regards toretrieving the queue entry. Such a set of requests completes deletion ofthe queue entry to remove the queue entry from the dispersed queue sincethe slice in error has been successfully rebuilt.

FIG. 45B is a flowchart illustrating an example of generating arebuilding task queue entry. The method begins at step 580 where aprocessing module (e.g., of scanning module) identifies a slice name ofa slice in error of a set of slices stored in a set of dispersed storage(DS) units. The identifying includes generating and outputting, to theset of DS units, a set of list slice requests to include a slice namerange to be scanned for errors, receiving list slice responses, andidentifying the slice name of the slice in error based on a comparisonof list slice responses. The method continues at step 582 where theprocessing module identifies a number of slice errors of the set ofslices (e.g., counting).

The method continues at step 584 where the processing module generates aqueue entry that includes the slice name of the slice in error, arebuilding task indicator (e.g., a rebuilding opcode), identity of theset of slices (e.g., the source name of the common set of slices), andthe number of slice errors. The method continues at step 586 where theprocessing module identifies a rebuilding dispersed queue based on thenumber of slice errors. The identifying may include one or more of alookup (e.g., a queue list by number of slice errors), a query, andreceiving. The method continues at step 588 where the processing modulefacilitates storing the queue entry in the identified rebuilding queuein another set of DS units. Alternatively, the processing modulefacilitates storage of the queue entry in the identified rebuildingqueue in the set of DS units.

The facilitating storage of the queue entry in the identified rebuildingqueue includes a series of steps. A first step includes generating a setof queue entry slice names based on one or more of a queue vaultidentifier, a queue name associated with the identified rebuildingqueue, a DS processing module identifier associated with the processingmodule, a client identifier based on a vault lookup, and a currenttimestamp. A second step includes encoding the queue entry using adispersed storage error coding function to produce a set of queue entryslices. A third step includes generating a set of write slice requeststhat includes the set of queue entry slices and the set of queue entryslice names. A fourth step includes outputting the set of write slicerequests to the other set of DS units when utilizing the other set of DSunits for storage of the queue entry.

In addition, a rebuilding module may remove a queue entry from a queueassociated with a highest number of missing slices first to facilitaterebuilding of the slice in error. When completing rebuilding of theslice in error, the rebuilding module facilitates deletion of the queueentry from the queue.

FIG. 46 is a flowchart illustrating another example of generating arebuilding task queue entry, that includes similar steps to FIG. 45B.The method begins with steps 580, 582, and 584 of FIG. 45B where aprocessing module (e.g., of a scanning module) identifies a slice nameof a slice in error of a set of slices stored in a set of dispersedstorage (DS) units, identifies a number of slice errors of the set ofslices, and generates a queue entry that includes the slice name of theslice in error, a rebuilding task indicator, identity of the set ofslices, and the number of slice errors.

The method continues at step 590 where the processing module generates avault source name based on the number of slice errors. The generatingincludes at least one of including a queue vault identifier (ID), aqueue name to include the number of slice errors, a DS processing moduleID, a client ID, and a timestamp of a current real-time. The methodcontinues at step 592 where the processing module facilitates storingthe queue entry in another set of DS units using the vault source name.The facilitating includes generating a set of slice names using thevault source name, encoding the queue entry to produce a set of queueentry slices, generating a set of write slice requests that includes theset of queue entry slices and the set of slice names, and outputting theset of write slice requests to the other set of DS units. In addition, arebuilding module may remove the queue entry that is associated with ahighest number of slices in error by generating a vault source name witha higher order queue name.

FIGS. 47A-B, E-H are schematic block diagrams of embodiments of adispersed storage network (DSN) illustrating examples of steps ofstoring data. The DSN includes the user device 14, the distributedstorage and task (DST) processing unit 16, and the network 24 of FIG. 1; and a set of DST execution units 1-n, where each DST execution unitmay be implemented with the DST execution unit 36 of FIG. 1 . The userdevice 14 includes a computing core 26 of FIG. 2 . The DST processingunit 16 includes the DST client module 34 of FIG. 3 . The DST clientmodule 34 includes the DST processing module 80 of FIG. 3 and a requestmodule 600. The request module 600 may be implemented utilizing aprocessing module 84 of FIG. 3 . Each DST execution unit includes theprocessing module 84 and the memory 88 of FIG. 3 .

FIG. 47A illustrates initial steps of the examples of the steps ofstoring the data. As a specific example, the request module 600receives, from the user device 14, a request 602 to store data A in theDSN. Having received the request 602, the request module 600 determines,for the request 602, dispersed storage error encoding parameters forencoding the data into sets of encoded data slices. The dispersedstorage error encoding parameters includes a per set decode threshold, aper set write threshold, and a per set total number. The per set decodethreshold indicates a number of encoded data slices of a set of encodeddata slices required to construct a corresponding segment of the data(e.g., where the data is divided into segments), the per set writethreshold indicates a number of encoded data slices of the set ofencoded data slices that are to be stored for a successful storageoperation, and the per set total number indicates the number of encodeddata slices in the set of encoded data slices (e.g., a pillar widthnumber). For example, the request module 600 determines the dispersedstorage error encoding parameters by determining a vault based on atleast one of the request 602 and the user device 14, and determining theper set decode threshold, the per set write threshold, and the per settotal number based on information regarding the vault (e.g., extractingparameters from a registry associated with the vault).

Having determined the dispersed storage error encoding parameters, therequest module 600 determines whether the request 602 includes a desiredwrite reliability indication. The desired write reliability indicationindicates a desired level of write reliability that meets or exceeds theper set write threshold. For example, desired write reliabilityindication includes a value in a range between the per set writethreshold and the per set total number. For instance, the desired levelof write reliability indication indicates 14 slices when the decodethreshold is 10, the write threshold is 12, and the total number is 16.More parameter examples are discussed in greater detail with referenceto FIG. 47C.

When the request 602 does not include the desired write reliabilityindication, the DST processing module 80 executes storage of the sets ofencoded data slices in accordance with the dispersed storage errorencoding parameters and may subsequently send storage reliabilityinformation to the user device 14 indicating how many encoded dataslices per set of encoded data slices were successfully stored. As aspecific example, the DST processing module 80 encodes the data using adispersed storage error coding function in accordance with the dispersedstorage error encoding parameters to produce the sets of encoded dataslices. For instance, the DST processing module 80 encodes a first datasegment of the data A to produce slices A-1-1, A-2-1, through A-n-1. TheDST processing module 80 issues, via the network 24, one or more sets ofwrite slice requests 604 to the set of DST execution units 1-n as writeslice requests 1-n, where the one or more sets of write slice requests604 includes the sets of encoded data slices. For each DST executionunit, the processing module 84 stores a corresponding encoded data slicein the memory 88 of the DST execution unit.

When the request 602 includes the desired write reliability indication,the DST processing module 80 executes the storage of the sets of encodeddata slices in accordance with the dispersed storage error encodingparameters and subsequently determines whether the storage of the setsof encoded data slices is meeting the desired write reliabilityindication. The determining whether the storage of the sets of encodeddata slices is meeting the desired write reliability indication isdiscussed in greater detail with reference to FIG. 47B.

FIG. 47B illustrates further steps of the examples of the steps ofstoring the data. As a specific example, while executing storage of thesets of encoded data slices in accordance with the dispersed storageerror encoding parameters, the DST processing module 80 determineswhether the storage of the sets of encoded data slices is meeting thedesired write reliability indication. For example, while the DSTprocessing module 80 executes the storage of the sets of encoded dataslices in accordance with the dispersed storage error encodingparameters, the DST processing module 80 enters a loop that includescausing the DST processing module 80 to determine whether the storage ofone of the sets of encoded data slices is meeting the desired writereliability indication. For instance, the DST processing module 80receives write slice responses 606, via the network 24, from write sliceresponses of write slice responses 1-n from the set of DST executionunits 1-n. Each write slice response indicates whether a correspondingencoded data slice was successfully stored in an associated DSTexecution unit. The DST processing module 80 indicates that the one setof encoded data slices is meeting the desired write reliabilityindication when a number of favorable (e.g., indicating successfulstorage) write slice responses 606 is greater than or equal to the valueof the write reliability indication.

When the storage of the one of the sets of encoded data slices is notmeeting the desired write reliability indication, the DST processingmodule 80 flags the one of the sets of encoded data slices anddetermines whether the one of the sets of encoded data slices is a lastset of the sets of encoded data slices (e.g., for all segments). Whenthe storage of the one of the sets of encoded data slices is meeting thedesired write reliability indication, the DST processing module 80determines whether the one of the sets of encoded data slices is thelast set of the sets of encoded data slices. When the one of the sets ofencoded data slices is not the last set of the sets of encoded dataslices, the DST processing module 80 repeats the loop for another one ofthe sets of encoded data slices. When the one of the sets of encodeddata slices is the last set, the DST processing module 80 exits theloop. When exiting the loop, the DST processing module 80 compiles alist of the sets of encoded data slices of all the sets of encoded dataslices that did not meet the desired write reliability indication toproduce a list of sets. Having produced the list of sets, the DSTprocessing module 80 determines a storage compliance process for thelist of sets and executes the storage compliance process for the sets ofencoded data slices based on the list of sets. The determining andexecution of the storage compliance process is discussed in greaterdetail with reference to FIGS. 47D and 47G.

When the storage of the set of encoded data slices is meeting thedesired write reliability indication, the request module 600 indicatesthat the set of encoded data slices met the desired write reliabilityindication by issuing storage of reliability information 608 withregards to data A to the user device 14. The reliability information 608includes one or more of a number of encoded data slices stored for eachsegment, an estimated storage reliability level for each data segment,an estimated storage reliability level for all data segments, a netstored indicator, a stored indicator, a stored with low reliabilityindicator, a stored with desired reliability indicator, and a storedwith high reliability indicator. The user device 14 may delete data Abased on the storage of reliability information 608. For example, theuser device 14 deletes data A from the computing core 26 when thestorage reliability information indicates that each data segment wasstored with the desired write reliability indication.

FIG. 47C is a diagram illustrating an example of a dispersed storage(DS) parameters table 610 that includes entries of a desired level field612 and corresponding entries of parameter sets of a decode thresholdfield 614, a write threshold field 616, a desired threshold field 618,and a total number field 620. The entries of the desired level field 612corresponds to names of candidate levels of the desired writereliability indication. For example, the candidate levels includes namesof a range from highest to lowest. A parameter set of entries of thedecode threshold field 614, the write threshold field 616, the desiredthreshold field 618, and the total number field 620 corresponds to oneof the candidate levels. For example, the highest desired level 612corresponds to a parameter set that includes a decode threshold entry of10, a write threshold of 12, a desired threshold value of 16, and atotal number of 16. As such, when the highest desired level is selected,the desired write reliability indication is met only when a value of thedesired threshold is 16. For instance, all 16 encoded data slices of aset of 16 encoded data slices were successfully stored to achieve thedesired write reliability indication. As another example, the mediumdesired level 612 corresponds to another parameter set that includes thedecode threshold entry of 10, the write threshold of 12, a desiredthreshold value of 14, and the total number of 16. As such, when themedium desired level is selected, the desired write reliabilityindication is met when the value of the desired threshold is 14 or more.For instance, the desired write reliability indication is achieved when14 or more encoded data slices of the set of 16 encoded data slices weresuccessfully stored.

FIG. 47D is a diagram illustrating an example of a storage compliancetable 622 that includes entries of the desired level field 612 of FIG.47C, an actual stored field 624, and a compliance process field 626. Anentry of the storage compliance table 622 may be utilized (e.g., by theuser device 14, by the DST processing module 80) to determine thestorage compliance process. As a specific example, a delete originalcompliance process 626 is selected when the highest desired level 612 isselected (e.g., requiring at least 16 successfully stored encoded dataslices per set) and the number of encoded data slices actually stored is16 (e.g., corresponding to an entry of 16 in the actual stored 624field). As such, the user device may delete the data being stored in theDSN. As another specific example, a re-store compliance process 626 isselected when the highest desired level 612 is selected and the numberof encoded data slices actually stored is 15. As such, the storagecompliance process includes retrying storage of the sets of encoded dataslices that were not successfully stored (e.g., missing one slice)during the execution of storage. As yet another example, a retryingslice compliance process 626 is selected when the medium-high desiredlevel 612 is selected (e.g., requiring at least 15 successfully storedencoded data slices per set) and the number of encoded data slicesactually stored is 14. As such, the storage compliance process includesinitiating a storage unit retry process for encoded data slices of theset of encoded data slices that were not successfully stored (e.g., 2slices) during the execution of storage.

As a further example, a re-store segment compliance process 626 isselected when the medium-high desired level 612 is selected (e.g.,requiring at least 15 successfully stored encoded data slices per set)and the number of encoded data slices actually stored is 13. As such,the storage compliance process includes initiating a storage unit retryprocess for the set of encoded data slices that were not successfullystored (e.g., all 16 slices) during the execution of storage. As a stillfurther example, a rebuild slice compliance process 626 is selected whenthe medium-high desired level 612 is selected (e.g., requiring at least15 successfully stored encoded data slices per set) and the number ofencoded data slices actually stored is 14. As such, the storagecompliance process includes initiating a rebuilding process for encodeddata slices of the set of encoded data slices that were not successfullystored (e.g., 4 slices) during the execution of storage.

FIG. 47E illustrates further steps of the examples of the steps ofstoring the data. As a specific example, the request module 600receives, from a user device 14, a request 602 to store data B in theDSN. The request module 600 determines, for the request 602 to storedata B, dispersed storage error encoding parameters for encoding thedata B into sets of encoded data slices. The dispersed storage errorencoding parameters includes the per set decode threshold, the per setwrite threshold, and the per set total number. Having determined theparameters, the request module 600 determines whether the request 602includes the desired write reliability indication. The DST processingmodule 80 encodes data B to produce the sets of encoded data slices andexecutes storage of the sets of encoded data slices in accordance withthe dispersed storage error encoding parameters (e.g., issuing one ormore sets of write slice requests 604, via the network 24, that includeswrite slice requests 1-n to the set of DST execution units 1-n).

FIG. 47F illustrates further steps of the examples of the steps ofstoring the data. As a specific example, when the request includes thedesired write reliability indication, while executing storage of thesets of encoded data slices in accordance with the dispersed storageerror encoding parameters, the DST processing module 80 determineswhether the storage of the sets of encoded data slices is meeting thedesired write reliability indication. For example, the DST processingmodule 80 receives write slice responses 606, via the network 24, thatincludes write slice responses of the write slice responses 1-n from theDST execution units 1-n, and determines whether the level of the desiredwrite reliability indication is being met. As a more specific example,the DST processing module 80 enters a loop where the DST processingmodule 80 determines whether the storage of one of the sets of encodeddata slices is meeting the desired write reliability indication. Whenthe storage of the one of the sets of encoded data slices is not meetingthe desired write reliability indication, the DST processing module 80flags the one of the sets of encoded data slices and determines whetherthe one of the sets of encoded data slices is a last set of the sets ofencoded data slices. When the one of the sets of encoded data slices isnot the last set of the sets of encoded data slices, the DST processingmodule 80 repeats the loop for another one of the sets of encoded dataslices. When the one of the sets of encoded data slices is the last setof encoded data slices, the DST processing module 80 exits the loop.

Having exited the loop, the DST processing module 80 compiles a list ofthe sets of encoded data slices that did not meet the desired writereliability indication to produce the list of sets. When storage of theset of encoded data slices of the sets of encoded data slices is notmeeting the desired write reliability indication, the DST processingmodule 80 determines a storage compliance process for the set of encodeddata slices to meet the desired write reliability indication. Forexample, the DST processing module 80 determines the storage complianceprocess for the list of sets. Having determined the storage complianceprocess, the DST processing module 80 executes the storage complianceprocess for the set of encoded data slices. For example, the DSTprocessing module 80 executes the storage compliance process for thesets of encoded data slices based on the list of sets. As a specificexample of executing the storage compliance process, the request module600 sends a message that includes the storage reliability information608 of data B to the user device 14 indicating that storage of the setof encoded data slices met the per set write threshold but did not meetthe desired write reliability indication.

FIG. 47G illustrates further steps of the examples of the steps ofstoring the data. As a specific example, continuing the steps of FIG.47F, the request module 600 receives a store data request 602 for data B(e.g., a response to the storage reliability information 608) from theuser device 14 requesting a storage retry of at least the encoded dataslices of the set of encoded data slices that were not successfullystored during the execution of storage. Having received the storagerequest 602, the DST processing module 80 retries storage of the encodeddata slices of the set of encoded data slices that were not successfullystored during the execution of storage. For example, the DST processingmodule 80 issues a set of write slice request 604, via the network 24,that includes a corresponding set of write slice requests 1-n to the setof DST execution units 1-n.

As another specific example of executing the storage compliance process,the DST processing module 80 initiates a rebuilding process for encodeddata slices of the set of encoded data slices that were not successfullystored during the execution of storage. As yet another specific exampleof executing the storage compliance process, the DST processing module80 initiates a storage unit retry process for encoded data slices of theset of encoded data slices that were not successfully stored during theexecution of storage.

FIG. 47H illustrates further steps of the examples of the steps ofstoring the data. As a specific example, when the request 602 tore-store at least a portion of data B includes the desired writereliability indication, while executing storage of the sets of encodeddata slices in accordance with the dispersed storage error encodingparameters, the DST processing module 80 determines whether the storageof the sets of encoded data slices is meeting the desired writereliability indication. For example, the DST processing module 80receives write slice responses 606, via the network 24, that includeswrite slice responses of the write slice responses 1-n from the DSTexecution units 1-n, and determines whether the level of the desiredwrite reliability indication is being met. When storage of the set ofencoded data slices is meeting the desired write reliability indication,the request module 600 issues the storage reliability information 608 tothe user device 14 to indicate that the set of encoded data slices metthe desired write reliability indication. The user device 14 may deletedata B from the computing core 26 when receiving the indication that theset of encoded data slices met the desired rate reliability indication.

FIG. 47I is a flowchart illustrating an achieving storage compliance.The method begins at step 630 where a processing module (e.g., ofdistributed storage and task (DST) client module) receives, from adevice (e.g., a user device), a request to store data in a dispersedstorage network (DSN). The method continues at step 632 where theprocessing module determines, for the request, dispersed storage errorencoding parameters for encoding the data into sets of encoded dataslices. The dispersed storage error encoding parameters includes a perset decode threshold, a per set write threshold, and a per set totalnumber. The per set decode threshold indicates a number of encoded dataslices of a set of encoded data slices required to construct acorresponding segment of the data, the per set write threshold indicatesa number of encoded data slices of the set of encoded data slices thatare to be stored for a successful storage operation, and the per settotal number indicates the number of encoded data slices in the set ofencoded data slices. As a specific example, the processing moduledetermines the dispersed storage error encoding parameters bydetermining a vault based on at least one of the request and the device,and determining the per set decode threshold, the per set writethreshold, and the per set total number based on information regardingthe vault.

The method continues at step 634 where the processing module determineswhether the request includes a desired write reliability indication. Thedesired write reliability indication indicates a desired level of writereliability that meets or exceeds the per set write threshold. Thedesired write reliability indication includes a value in a range betweenthe per set write threshold and the per set total number. As a specificexample, the desired write reliability indication indicates a level of14 encoded data slices when the write threshold is 12 and the totalnumber is 16. When the request includes the desired write reliabilityindication, the method branches to step 638. When the request does notinclude the desired write reliability indication, the method continuesto step 636.

When the request does not include the desired write reliabilityindication, the method continues at step 636 where the processing moduleexecutes storage of the sets of encoded data slices in accordance withthe dispersed storage error encoding parameters. As a specific example,the processing module issues sets of write slice requests to the DSNmemory, where the sets of write slice requests includes the sets ofencoded data slices, receives write slice responses regarding status ofstorage of the sets of encoded data slices, and issues a status messageto the device indicating status of storage of the sets of encoded dataslices (e.g., successful with regards to the write threshold, notsuccessful with regards to the write threshold, number of encoded dataslices successfully stored per set of encoded data slices, an estimatedstorage reliability level).

When the request includes the desired write reliability indication, themethod continues at step 638 where the processing module executesstorage of the sets of encoded data slices and while executing storageof the sets of encoded data slices in accordance with the dispersedstorage error encoding parameters, determines whether the storage of thesets of encoded data slices is meeting the desired write reliabilityindication. The method branches to step 642 when the storage is notmeeting the desired write reliability indication. The method continuesto step 640 when the storage is meeting the desired write reliabilityindication. As a specific example, while executing the storage of thesets of encoded data slices in accordance with the dispersed storageerror encoding parameters, the processing module enters a loop thatincludes determining whether the storage of one of the sets of encodeddata slices is meeting the desired write reliability indication. Whenthe storage of the one of the sets of encoded data slices is not meetingthe desired write reliability indication, the processing module flagsthe one of the sets of encoded data slices and determines whether theone of the sets of encoded data slices is a last set of the sets ofencoded data slices. Alternatively, when storage of the one of the setsof encoded data slices is meeting the desired write reliabilityindication, the processing module determines whether the one of the setsof encoded data slices is the last set of the sets of encoded dataslices. When the one of the sets of encoded data slices is not the lastset of encoded data slices, the processing module repeats the loop foranother one of the sets of encoded data slices. When the one of the setsof encoded data slices is the last set of encoded data slices, theprocessing module exits the loop. When exiting the loop, the processingmodule compiles a list of the sets of encoded data slices of all thesets of encoded data slices that did not meet the desired writereliability indication to produce a list of sets.

When storage of the set of encoded data slices is meeting the desiredwrite reliability indication, the method continues at step 640 where theprocessing module indicates that the set of encoded data slices met thedesired write reliability indication. When storage of the set of encodeddata is not meeting the desired write reliability indication, the methodcontinues at step 642 where the processing module determines a storagecompliance process for the set of encoded data slices to meet thedesired write reliability indication. As a specific example, theprocessing module determines the storage compliance process for the listof sets. Having determined the storage compliance process, the methodcontinues at step 644 where the processing module executes the storagecompliance process for the set(s) of encoded data slices based on thelist of sets.

As a specific example of executing the storage compliance process, theprocessing module initiates a rebuilding process for encoded data slicesof the set of encoded data slices that were not successfully storedduring the execution of storage. For instance, the processing moduleissues a rebuilding request to a rebuilding entity that includesidentification of the set of encoded data slices that were notsuccessfully stored during the execution of storage. As anotherinstance, the processing module retrieves at least a decode thresholdnumber of encoded data slices of the set of encoded data slices thatwere not successfully stored, decodes the at least a decode thresholdnumber of encoded data slices to reproduce a data segment, encodes thedata segment using the dispersed storage error coding function toreproduce the set of encoded data slices, and stores the set of encodeddata slices in the DSN memory.

As another specific example of executing the storage compliance process,the processing module initiates a storage unit retry process for encodeddata slices of the set of encoded data slices that were not successfullystored during the execution of storage. For instance, the processingmodule issues a redundant write slice request to a corresponding storageunit of the DSN memory for each encoded data slice of the set of encodeddata slices that were not successfully stored.

As yet another specific example of executing the storage complianceprocess, the processing module sends a message to the device indicatingthat storage of the set of encoded data slices met the per set writethreshold but did not meet the desired write reliability indication. Theprocessing module receives a response from the device requesting astorage retry of at least the encoded data slices of the set of encodeddata slices that were not successfully stored during the execution ofstorage. Having received the response, the processing module retriesstorage of the encoded data slices of the set of encoded data slicesthat were not successfully stored during the execution of storage. Forinstance, the processing module encodes a portion of the data using thedispersed storage error coding function to reproduce the set of encodeddata slices that were not successfully stored. Having reproduced the setof encoded data slices, the processing module sends the encoded dataslices of the set of encoded data slices to the DSN memory for storage.

FIG. 48A is a schematic block diagram of another embodiment of adispersed storage system that includes a dispersed storage (DS)processing module 422 and a DS unit set 424. The DS unit set 424includes a set of DS units 426 utilized to access slices stored in theset of DS units 426. The DS processing module 422 may be implementedutilizing at least one of a distributed storage and task (DST) clientmodule, a DST processing unit, a DS processing unit, a user device, aDST execution unit, and a DS unit. Alternatively, another DS processingmodule may be utilized to store data in the DS unit set 424 as aplurality of encoded data slices associated with a plurality of slicenames. The system is operable to facilitate deletion of data in the DSunit set 424.

The DS processing module 422 identifies a data object stored locally(e.g., in a cache memory of the DS processing module 422) where thelocally stored data object is associated with the plurality of sets ofencoded data slices stored in the DS unit set 424. The DS processingmodule 422 determines a threshold number (e.g., greater than a readthreshold number) of slice names corresponding to at least a set ofencoded data slices of the plurality of sets of encoded data slicescorresponding to the locally stored data object. The threshold number ofslice names may be associated with a preferred DS units of the set of DSunits 426 where the preferred DS units are associated with a preferredperformance levels (e.g., more available processing capacity) ascompared to other DS units of the DS unit set.

The DS processing module 422 generates a threshold number of watchrequests 650 that includes the threshold number of slice names. The DSprocessing module 422 outputs the threshold number of watch requests 650to corresponding DS units of the DS unit set 424. Each DS unit 426 ofthe corresponding DS units generates a watch response 652 with regardsto availability of a corresponding encoded data slice. For example, theDS unit 426 generates the watch response 652 to indicate that theencoded data slice is visible when the DS unit 426 received a writeslice request and a commit request with regards to the encoded dataslice. The DS unit 426 outputs the watch response 652 to the DSprocessing module 422.

The DS processing module 422 receives watch responses 652 from the DSunit set 424. The DS processing module 422 determines whether to deletethe locally stored data object based on the watch responses. Forexample, the DS processing module 422 determines to delete the locallystored object when a threshold number of favorable (e.g., encoded dataslice is visible) watch responses 652 have been received. The method ofoperation is discussed in greater detail with reference to FIG. 48B.

FIG. 48B is a flowchart illustrating an example of deleting data. Themethod begins with step 654 where a processing module (e.g., of adispersed storage (DS) processing module) identifies a data object, thatis cached locally, for deletion. The identifying may be based on one ormore of a memory utilization level indicator, an error message, arequest, an expiration time, and a storage age indicator. The methodcontinues at step 656 where the processing module identifies a thresholdnumber of slice names corresponding to encoded data slices stored at acorresponding threshold number of DS units corresponding to some of thedata object. The identifying includes at least one of selecting thethreshold number of DS units based on one or more of a round-robinselection scheme, a DS unit activity indicator, an error message, and apredetermination. The identifying further includes generating one ormore sets of slice names corresponding to the data object based on adata object identifier and selecting one or more subsets of slice nameswhere each subset includes a threshold number of slice names.

The method continues at step 658 where the processing module generates athreshold number of watch requests that includes the threshold number ofslice names. The method continues at step 660 where the processingmodule outputs the threshold number of watch requests to the thresholdnumber of DS units where each DS unit of the threshold number of DSunits generates and outputs a watch response to indicate whether statusof a corresponding encoded data slice has changed from not visible tovisible. The watch response includes a slice name and a visibilitystatus indicator. When receiving a threshold number of favorable (e.g.,including visibility status indicator indicating that an associatedencoded data slice is visible) watch responses, the method continues atstep 662 where the processing module deletes the data object.

FIG. 49A is a schematic block diagram of another embodiment of adispersed storage system that includes a dispersed storage (DS)processing module 422 and a DS unit set 424. The DS unit set 424includes a set of DS units 426 utilized to access slices stored in theset of DS units 426. The DS processing module 422 may be implementedutilizing at least one of a distributed storage and task (DST) clientmodule, a DST processing unit, a DS processing unit, a user device, aDST execution unit, and a DS unit. The system is operable to facilitateaccess of data in the DS unit set 424.

The DS processing module 422 stores data as a plurality of encoded dataslices in the DS unit set 424 and retrieves at least some of the encodeddata slices from the DS unit set 424 to reproduce the data. The DSprocessing module 422 issues one or more sets of slice access requests664 to the DS unit set 424 to store the encoded data slices in the DSunit set 424. A slice access request 664 may include one or more of arequest type indicator, a slice name 666, and an encoded data slice. Forexample, the slice access request 664 includes a write slice requesttype (e.g., write, read, delete, list), the encoded data slice, and theslice name 666 corresponding to the encoded data slice when storing theencoded data slice in a DS unit 426 of the DS unit set 424.

The DS processing module 422 issues another one or more sets of sliceaccess requests 664 to the DS unit set 424 to retrieve the encoded dataslices from the DS unit set 424 where a slice access request 664 of theother one or more sets of slice access requests 664 includes a readslice request type and the slice name 666 corresponding to the encodeddata slice associated with the retrieving. The DS processing module 422receives a slice access response 668 from one or more DS units 426 ofthe DS unit set 424 in response to the slice access request 664 thatincludes the read slice request type. The slice access response 668includes one or more of the request type indicator, the slice name 666,the encoded data slice, and a status code. The status code indicatesstatus of a requested operation of a slice access request. For example,the status code indicates whether the requested operation wassuccessful.

The slice name 666 utilized in the slice access request 664 and theslice access response 668 includes a slice index field 670 and a vaultsource name field 672. The slice index field 670 includes a slice indexentry that corresponds to a pillar number of a set of pillar numbersassociated with a pillar width dispersal parameter utilized in adispersed storage error coding function to encode data to produceencoded data slices. The vault source name field 672 includes a sourcename field 674 and a segment ID field 676. The segment ID field 676includes a segment ID entry corresponding to each data segment of theplurality of data segments that comprise the data. The source name field674 includes a vault identifier (ID) field 678, a generation field 680,and an object ID field 682. The vault ID field 678 includes a vault IDentry that identifies a vault of the dispersed storage system associatedwith the requesting entity. The generation field 680 includes ageneration entry corresponding to a generation of a data set associatedwith the vault. Multiple generations of data may be utilized for thevault to distinguish major divisions of a large amount of data. Theobject ID field 682 includes an object ID entry that is associated witha data name corresponding to the data.

As a specific example of storing the data, the DS processing module 422receives the data and the data name associated with the data. The DSprocessing module 422 segments the data to produce a plurality of datasegments in accordance with a segmentation scheme. The DS processingmodule 422 generates a set of slice names 666 for each data segment ofthe plurality of data segments. The generating includes a series ofsteps. In a first step, the DS processing module 422 identifies a vaultID based on the request. For example, the DS processing module performsa registry lookup to identify the vault ID based on a requesting entityID associated with the request. In a second step, the DS processingmodule 422 generates a generation field entry based on utilization ofother generation entries associated with the vault ID. The DS processingmodule selects a generation ID associated with a generation that is notyet full and is just greater than a previous generation ID correspondingto a generation that is full. For example, the DS processing module 422accesses a generation utilization list of a registry to identify afullness level associated with each potential generation ID to identifya generation ID that is not full and is just one generation ID largerthan a previous generation ID that is full. In a third step, the DSprocessing module 422 generates an object ID entry. The generatingincludes at least one of generating an object ID based on a randomnumber, performing a deterministic function (e.g., a hashing function)on the data name to produce the object ID entry, and performing thedeterministic function on at least a portion of the data to produce theobject ID entry. In a fourth step, for each data segment, the DSprocessing module 422 generates a set of slice names 666 where eachslice name 666 includes a slice index entry corresponding to a pillarnumber of the slice name, the vault ID entry, the generation entry, theobject ID entry, and a segment number corresponding to the data segment(e.g., starting at zero and increasing by one for each data segment).

Having generated the set of slice names 666, the DS processing module422 encodes the plurality of data segments to produce a plurality ofsets of encoded data slices using a dispersed storage error codingfunction. The DS processing module 422 generates one or more sets ofslice access requests 664 that includes the sets of slice names 666 andthe plurality of sets of encoded data slices. The DS processing module422 outputs the one or more sets of slice access requests 664 to the DSunit set 424.

As a specific example of retrieving the data, the DS processing module422 receives the data name associated with the data for retrieval. TheDS processing module 422 obtains one or more source names associatedwith the data. The obtaining includes identifying the vault ID (e.g.,based on a registry lookup, a dispersed storage network (DSN) indexlookup based on the data name), identifying the object ID (e.g., a DSNindex lookup based on the data name, performing a deterministic functionon the data name), and selecting one or more generation field entries.The selecting of the one or more generation field entries includesidentifying a fullness level associated with each viable generationfield entry and selecting the one or more generation field entries basedon the fullness levels of each of the one or more generation fieldentries. For example, the DS processing module 422 accesses thegeneration utilization list and selects generation field entriesassociated with each generation that is full and a next generation IDthat is not full where the next generation ID is one greater than agreatest generation ID of generation IDs associated with fullgenerations. For each generation of the one or more generation fieldentries, the DS processing module 422 generates the one or more sourcenames that includes the generation, the vault ID, and the object ID.

Having generated the one or more source names, the DS processing module422 generates, for each source name, one or more sets of slice namesthat includes the source name, a slice index, and a segment ID of the atleast one data segment of the plurality of data segments. The DSprocessing module 422 generates one or more sets of slice accessrequests 664 that includes read slice requests and the one or more setsof slice names. The DS processing module 422 outputs the one or moresets of slice access requests 664 to the DS unit set 424. The DSprocessing module 422 receives the slice access responses 668 from theDS unit set 424 and decodes the received slice access responses 668using the dispersed storage error coding function to reproduce the data.The decoding includes utilizing at least a decode threshold number offavorable (e.g., successfully retrieved an encoded data slice) sliceaccess responses 668 corresponding to a common data segment of a commongeneration. Alternatively, the DS processing module 422 attempts toretrieve a first data segment using multiple generation IDs to identifyone generation ID of the multiple generation IDs associated with storageof the data for utilization of the one generation ID in retrieval ofsubsequent data segments. The method of operation is discussed ingreater detail with reference to FIG. 49B.

FIG. 49B is a flowchart illustrating another example of accessing data.The method begins with step 684 where a processing module (e.g., adispersed storage (DS) processing module) identifies a data objectaccess within a dispersed storage network (DSN). The identifying may bebased on receiving a request that includes one or more of a data name, arequester identifier (ID), a vault ID, an object ID, a source name, anddata. The method continues at step 686 where the processing moduleidentifies a vault ID based on the data object. For example, theprocessing module performs a vault ID lookup based on the data name. Asanother example, the processing module performs the vault ID lookupbased on the requester ID.

The method continues at step 688 where the processing module obtains anobject ID based on the data object. The obtaining further includesobtaining the object ID based on one or more of a request type, thedata, receiving the object ID, and the data name. For example, for aread request, the processing module accesses a DSN index (e.g., adirectory) to retrieve the object ID based on the data name. As anotherexample, for a write request, the processing module generates the objectID based on a deterministic function applied to the data name.

The method continues at step 690 where the processing module selects atleast one generation ID based on generation status. The generationstatus indicates availability of one or more generation IDs (e.g., fullor not full). The selecting further includes selecting the generation IDbased on one or more of the request type and the generation status. Forexample, for a read request, the processing module selects eachgeneration ID associated with a generation status that indicates thatthe generation is full and selects a generation ID that is one greaterthan a largest generation ID of one or more generation IDs that arefull, if any. As another example, for a write request, the processingmodule selects a lowest generation ID associated with a generation thatis not full.

For each generation ID, the method continues at step 692 where theprocessing module generates at least one set of slice names using thevault ID, generation ID, and the object ID. For each set of slice names,the method continues at step 694 where the processing module generates aset of slice access requests that includes the set of slice names. Thegenerating may further be based on the request type. For example, for awrite request, the processing module includes a set of slice names andincludes a set of encoded data slices that are encoded, using adispersed storage error coding function, from a corresponding datasegment of the data. As another example, for a read request, theprocessing module includes a set of slice names.

The method continues at step 696 where the processing module accessesthe DSN utilizing the set of slice access requests. The accessingincludes outputting the set of slice access requests to the DSN. Theaccessing may further be based on the request type. For example, for theread request type, the processing module receives slice access responsesand decodes favorable slice access responses using the dispersed storageerror coding function to reproduce one or more data segments of thedata. As another example, for the write request type, the processingmodule confirms storage of the data object when receiving a writethreshold number of favorable slice access responses from the DSN foreach data segment of a plurality of data segments of the data.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by a processing system that includes a processing circuit, the method comprises: receiving a write request to store a data object; selecting a selected memory type of a plurality of memory types to store the data object, based on object parameters associated with the data object; selecting a selected memory device to store the data object, the selected memory device having the selected memory type of the plurality of memory types; and storing the data object in the selected memory device having the selected memory type of the plurality of memory types, wherein the data object is dispersed error encoded and stored as a plurality of encoded data slices.
 2. The method of claim 1, wherein the object parameters include a size indicator associated with the data object.
 3. The method of claim 1, wherein the object parameters include a temporary storage identifier associated with the data object.
 4. The method of claim 1, wherein the plurality of memory types include a first memory type and a second memory type and wherein the first memory type has a lower latency compared with the second memory type.
 5. The method of claim 4, wherein the plurality of memory types include a first memory type and a second memory type and wherein the first memory type has a lower cost compared with the second memory type.
 6. The method of claim 1, wherein the selected memory type includes a temporary storage and the selected memory device is a solid state memory device, and wherein the temporary storage has a lower latency compared to other memory devices associated with at least one other memory type.
 7. The method of claim 1, wherein the selected memory type includes a temporary storage and the selected memory device is a solid state memory device, and wherein the temporary storage has a lower access latency compared to other memory devices associated with at least one other memory type.
 8. The method of claim 1, wherein the selected memory type includes a main memory space.
 9. The method of claim 6, wherein the the selected memory device is a random access memory device.
 10. The method of claim 1, wherein the data object is dispersed error encoded into a plurality of data slices.
 11. A processing system of a storage network comprises: at least one processor; a memory that stores operational instructions, that when executed by the at least one processor cause the processing system to operations including: receiving a write request to store a data object; selecting a selected memory type of a plurality of memory types to store the data object, based on object parameters associated with the data object; selecting a selected memory device to store the data object, the selected memory device having the selected memory type of the plurality of memory types; and storing the data object in the selected memory device having the selected memory type of the plurality of memory types, wherein the data object is dispersed error encoded and stored as a plurality of encoded data slices.
 12. The processing system of claim 11, wherein the object parameters include a size indicator associated with the data object.
 13. The processing system of claim 11, wherein the object parameters include a temporary storage identifier associated with the data object.
 14. The processing system of claim 11, wherein the memory type includes a temporary storage.
 15. The processing system of claim 14, wherein the selected memory device is a solid state memory device.
 16. The processing system of claim 14, wherein the temporary storage has a lower latency compared to other memory devices associated with at least one other memory type.
 17. The processing system of claim 14, wherein the temporary storage has a lower access latency compared to other memory devices associated with at least one other memory type.
 18. The processing system of claim 11, wherein the memory type includes a main memory space.
 19. The processing system of claim 16, wherein the the selected memory device is a random access memory device.
 20. The processing system of claim 11, wherein the data object is dispersed error encoded into a plurality of data slices. 